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EP2211300B1 - Method of forecasting electricity production of photovoltaic means - Google Patents

Method of forecasting electricity production of photovoltaic means Download PDF

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Publication number
EP2211300B1
EP2211300B1 EP10150771.3A EP10150771A EP2211300B1 EP 2211300 B1 EP2211300 B1 EP 2211300B1 EP 10150771 A EP10150771 A EP 10150771A EP 2211300 B1 EP2211300 B1 EP 2211300B1
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EP
European Patent Office
Prior art keywords
forecasting
electrical production
photovoltaic device
production
photovoltaic
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EP10150771.3A
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German (de)
French (fr)
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EP2211300A1 (en
Inventor
Xavier Le Pivert
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Commissariat a lEnergie Atomique et aux Energies Alternatives CEA
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Commissariat a lEnergie Atomique et aux Energies Alternatives CEA
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy

Definitions

  • the invention relates to a method for predicting the electrical output of a photovoltaic device. It also relates to a software implementation of such a method and a photovoltaic device implementing such a method. Finally, it relates to a use of this method for diagnosing a photovoltaic device.
  • a general object of the invention is to provide a more accurate and reliable solution for predicting the electrical output of a photovoltaic device.
  • the invention also relates to a computer medium comprising software capable of implementing the method for predicting the electrical production of a photovoltaic device as described above.
  • the invention also relates to a photovoltaic device comprising photovoltaic modules, an element for measuring their actual electrical production, characterized in that it comprises a management unit implementing the electricity production forecasting method as described above. .
  • the invention also relates to the use of the method for predicting the electrical output of a photovoltaic device as described above for diagnosing the state of a photovoltaic device.
  • the figure 1 schematically represents a photovoltaic device according to an embodiment of the invention.
  • This device comprises several photovoltaic modules 1 connected to the traditional electrical network 3 via an inverter 2.
  • the modules can of course be connected to an autonomous application via a converter.
  • This device further comprises a control unit or management 10 based on a computer comprising software that implements the electric power forecasting method which will be described below.
  • the control unit 10 receives the measurement of the actual electricity production of the photovoltaic installation 1, 2 via a link 4.
  • this control unit 10 receives as input by a communication means 6 the forecast data. meteorological conditions established by a meteorological forecasting entity 5.
  • the control unit 10 thus implements a method for predicting the electrical production of the photovoltaic device, which is based on various blocks represented in FIG. figure 2 .
  • This control unit can be located on the site of the photovoltaic device or remote from this site. It may consist of software and / or hardware calculation means (software and / or hardware), one or more storage means for storing the information to be processed and communication means.
  • Block 20 implements weather forecasts. This preliminary part is performed by a meteorological entity 5 external to the photovoltaic production device, according to all methods: the invention does not relate specifically to this block.
  • the results obtained by this block 20 are transmitted by the communication means 6 to the control unit 10 of the photovoltaic device.
  • These data 25, which particularly comprise the irradiation or the illumination and the ambient temperature, represent the essential inputs of the process of estimation of the electrical production which will be implemented by the management unit 10, and which is based on four blocks 30, 40, 50, 60 which will now be described.
  • the first block 30 implements the calculation of local meteorological forecasts that are more refined than those transmitted by the meteorological entity 5. For this purpose, it uses interpolation methods and / or statistical correlations and / or data bases. historical prediction and meteorological meteorological data to obtain meteorological forecast quantities, such as illumination in a horizontal plane and temperature, with a finer spatial and temporal pitch than that of meteorological data. received from the block 20. In fact, these forecasts 25 transmitted by the block 20 are generally in a mesh of several kilometers and a time step of several hours, which is insufficient at the scale of a photovoltaic production site . The calculations implemented in this first block 30 are therefore based on a first calculation model.
  • the results 45 obtained by the second block 40 are then used by a third block 50 which finally calculates an estimate of the electrical production 55 of the photovoltaic device according to its performances, which are modeled by a coefficient of losses, or by a yield, which can be a function of the temperature and the lighting.
  • All the preceding blocks are initially based on various theoretical and / or empirical approaches that may belong to the state of the art.
  • the results 35, 45, 55 obtained at each step show some error and uncertainty.
  • at least one of the three models, preferably all three, implemented by the blocks 30, 40, 50, respectively, is improved from the direct or indirect comparison between the measurement of the actual electricity production. and the value of production estimated over a given period, and according to the sunny situation or not of the same period.
  • Block 60 thus implements an essential first step E1 of the invention which consists in determining whether a past day considered is sunny or not.
  • the concept of the invention is to consider that if the day is sunny, the results obtained by the blocks 30 and 40 of the method of the invention are correct, that is to say that the estimated illumination in the plane of photovoltaic modules is right.
  • the error noted on the value of the forecast of the electrical production by the method, by its comparison with the real value as measured, is then only caused by the inaccuracy of the third calculation model implemented at the level of the third block 50. This approach amounts to considering that in sunny weather, the error committed by the first two blocks 30, 40 is negligible compared to that made by the third block 50.
  • This learning concept has the advantage of allowing the empirical improvement of the calculation models implemented by the method from the sole measurement of the actual production obtained for the photovoltaic device. It does not require several different measures for the separate treatment of the various process blocks, and for example does not require a sunshine sensor such as a pyranometer, which is relatively expensive.
  • the first step E1 of determining the type of day, sunny or cloudy will now be described.
  • the principle of this determination is based on a comparison between electricity production on the one hand measured, based on a series of measurements E11 for example with a periodicity of between 1 second and 10 minutes, and the same series obtained for the theoretical electricity production on a clear day, making the assumption of clear weather, preferably according to a frequency in phase with the series of measurements.
  • a first sub-step consists of determining the E12 illumination forecast series in the plane of the photovoltaic modules on a clear day by any existing model, for example with that set implemented in the management unit 10. This series can also be corrected from weather forecasts.
  • a series of ambient temperatures is established E13, either by measurement, or by calculation using models, or from weather forecasts.
  • the photovoltaic production in clear weather E14 is then calculated with block 50 of the process of the management unit 10 of the photovoltaic device, from these series of values of illumination and temperature, taking into account the losses or performances. at the level of the photovoltaic modules as evaluated by the model implemented at the level of the management unit 10.
  • the day should be considered sunny or cloudy.
  • This qualification is implemented by the detection of possible cloudy passages, which is easily detectable since the illumination, and therefore the power output, then decreases by about 80%.
  • the day will not be considered cloudy if there is only one short cloudy passage.
  • a predefined threshold sets a limit between a day that will be considered a sunny day and a cloudy day.
  • This last stage of qualification is complicated by the fact that a shadow zone on the photovoltaic modules can be caused by the environment of the device photovoltaic, like a building shading at a certain time, and not a cloudy passage. The method therefore distinguishes between the passage of a cloud and such shading.
  • the method of defining the type of day is based not only on the analysis of the ratio between the measured electrical power and the theoretical electrical power on a clear day E15, but also on the analysis of the derivative of this ratio E16, for take into account the speed of variation of this ratio.
  • Two time series are thus obtained, from which anomalous events are detected, defined by a certain predefined threshold. As soon as the amount of abnormal events exceeds a certain threshold E17, the day is considered as not sunny, and otherwise it is sunny.
  • the preceding method can be simplified by implementing only one of the two analysis steps E15, E16.
  • the method could include a preliminary stage of detection of masks, that is to say natural obstacles such as mountains, buildings, ..., which create shading at the photovoltaic modules, at least some periods of the year.
  • the Figures 3 to 5 illustrate a first example of implementation of step E1 described above.
  • the figure 3 represents two curves 70, 71 respectively corresponding to the measured and theoretical electrical power on a clear day on a day according to a first scenario.
  • the figure 4 represents the ratio 72 between the electric power measured on the theoretical electrical power on a clear day as a function of time for this scenario.
  • a rectangular zone 73 corresponds to a threshold beyond which the event is considered abnormal.
  • the domain 73 called "sunny day” is defined for a value of the power ratio 72 between 0.5 and 1.
  • the figure 5 illustrates the curve 74 of the absolute value of the derivative of the power ratio as a function of time.
  • a rectangular zone 75 defined by a value of this ratio between 0 and 0.1 corresponds to a sunny day situation.
  • the two curves 72, 74 of the power ratio measured on the theoretical power on a clear day and the absolute value of its derivative very rarely leave the sunny areas 73, 75. The day considered by this scenario is therefore considered like a sunny day.
  • the Figures 6 to 8 illustrate a second example of implementation of step E1 described above.
  • the figure 6 represents two curves 70 ', 71' respectively corresponding to the electrical power measured and theoretical on a clear day according to a second scenario of one day.
  • the figure 7 represents as a function of time the ratio 72 'between the electric power measured on the theoretical electrical power on a clear day for this scenario.
  • the rectangular zone 73 ' corresponds to a sunny situation, for a value of the power ratio 72' of between 0.5 and 1.
  • the figure 8 illustrates the curve 74 'of the absolute value of the derivative of the power ratio as a function of time.
  • the method for predicting the electrical output of the photovoltaic device implements a second step E2 which distinguishes two situations as a function of the result of the first step E1.
  • the first part of the calculation of the process implemented by the first two blocks 30, 40 is correct, it is that is, the illumination provided in the plane of the photovoltaic modules has a satisfactory result, the error of which is negligible.
  • This illumination is therefore considered as actual illumination, equivalent to that which would be obtained from a measurement.
  • the error found between the actual measured electricity production and that predicted by the process depends solely on the third calculation model implemented by the third block 50 of the process.
  • This calculation consists in determining the production of the photovoltaic device as a function of the illumination, taking into account power losses as a function of temperature.
  • the error observed is used to correct this third model of calculation, by correcting the coefficient of losses used in this third model.
  • This correction can be done every sunny day, by immediately modifying the coefficient of losses of the model in order to reuse it immediately for the future implementations of the process.
  • the recalculated loss coefficient can be stored in a memory of the management unit 10, and serve as a basis for a periodic recalculation of a new loss coefficient from these stored values, as a simple average of these values for example.
  • the new value of the loss coefficient then replaces the previous value for future calculations of electricity production forecasts.
  • teaching sunny days allows the learning of the third model used in the electricity production forecasting process, the other calculation models implemented in this process remaining unchanged during these periods of sunny days.
  • the Figures 9 to 13 illustrate an example of implementation of this second step E2 in the case of a sunny day.
  • the Figures 9 and 10 respectively illustrate the curves 76 and 77 of illumination and temperature obtained as a function of time according to the chosen scenario.
  • the figure 11 illustrates the measured production and expected production curves 79 as a function of time during that day.
  • the difference between the two preceding curves makes it possible to determine the losses as a function of the ratio of the expected power to the nominal power, which are represented by the curves 80 on the figure 12 .
  • These losses are modeled by a polynomial represented by the curve 81 of this same figure.
  • These losses thus obtained and modeled make it possible to modify the coefficient of losses of the third model of calculation of the method of provision of the invention.
  • a new expected production curve 82 is obtained, much closer than the initial curve 79 of the measured production curve 78, as illustrated in FIG. figure 13 .
  • the third model of calculation of the process is correct, that is to say that the electrical production calculated according to the illumination in the plane of the photovoltaic modules presents a satisfactory result, of which the error is negligible.
  • the error observed between the actual measured electricity production and that estimated by the method depends solely on the first two calculation models implemented by the method, as described with reference to at least one of the first two blocks 30, 40.
  • the actual electrical production is measured then by applying a calculation inverse to the calculation implemented in the third block 50, a "virtual or indirect measure", ie an indirect real value, of the illumination that is received by the photovoltaic modules.
  • the first part of the model including the first two calculation models implemented in the blocks 30 and 40 allows on the other hand to calculate an estimated illumination from the weather forecasts. These measured and estimated illuminances are compared and their difference serves as a starting point for a correction of at least one of the two calculation models of the first two blocks 30, 40 of the method.
  • This correction can consist of different solutions. First, it can relate to only one of the two calculation models implemented or both. Then, it can be based on a computation of correlations between weather forecasting and local illumination, by a statistical approach or by neural networks.
  • the second calculation model implemented in the second block 40 of the method is considered reliable.
  • the correction step then consists in improving only the first calculation model implemented in the first block 30 of the method, which consists of an extrapolation of the meteorological data in order to obtain an estimate of the illumination in a horizontal plane.
  • the actual illumination in a horizontal plane is virtually known, by an inverse calculation of the second model of computation from the illumination in the plane of the photovoltaic modules which is deduced from the measurement of the real electrical production, as has been made explicit. above. It is therefore an illumination that can be described as a virtual measure, since it is indirectly measured by the measurement of real electricity production. Then, the comparison between this virtual illuminance measured and that estimated by the process serves as a basis for improving the first calculation model of the process.
  • the Figures 14 to 17 illustrate an example of implementation of this second step E2 in the case of a cloudy day.
  • the figure 14 illustrates the curve 83 of the electricity production measured during the cloudy day.
  • the figure 15 shows respectively the curves 84 and 85 of the illuminations in the plane of the photovoltaic modules and in the horizontal plane as a function of time according to the chosen scenario.
  • the figure 16 illustrates points 86 representing the illumination as a function of time resulting from the four-point weather forecast around the photovoltaic production device, while the points 87 represent these same virtually measured illuminations. It was chosen here to select the four meteorological data points that are closest to the production site. It is then possible to deduce the illumination on the site for example by applying a weighting of each of the four points obtained by the meteorological data.
  • the corresponding weights are determined and improved according to the database of measurements made in cloudy weather. They can be calculated by purely statistical methods, by artificial intelligence, etc. This database is used to recalculate the weights to obtain a more precise result. So, the figure 17 illustrates the evolution over several months of the four weights considered according to the irradiation envisaged in the four points considered.
  • the learning mechanism has been described on the basis of a time division at the scale of one day. However, any other temporal division would be possible. For example, it is possible to follow the same principle on the basis of half a day, first determining whether this half-day is sunny or cloudy, then continuing the rest of the process. On the other hand, the learning mechanism can be implemented over all these periods, or only a part of these periods according to predefined criteria, such as only the periods for which measurements of the electrical production of the photovoltaic device are available with sufficient frequency. In addition, it can be chosen to implement this learning mechanism for a limited time, predefined, or this mechanism can be implemented permanently, unlimited.
  • the invention preferably makes it possible to improve the three main calculation models of the method, implemented within the three blocks 30, 40, 50. However, its use for any one of these three blocks already makes it possible to improve the processes existing and does not escape the concept of the present invention.
  • the invention is advantageous in that it leads to a method for predicting the improved electrical output using the only measurement of actual electricity production.
  • this concept of the invention can be combined with any other empirical correction system calculation models, implemented on the basis of other measurements for example, without departing from the concept of the invention.
  • the invention has been described using certain important quantities such as illumination, which represents a received power per unit area.
  • other neighboring quantities make it possible to implement the same calculations and the same method, such as, for example, irradiation, which represents the energy received per unit area. It is possible to switch from irradiance to irradiation by simple conversion and the use of one or other of these magnitudes in the process represents equivalent solutions.
  • the method of the invention has been presented according to an abstract division into different blocks 30, 40, 50, 60 to facilitate its understanding. However, it represents an indissociable whole whose different elements can be nested in a more complex way. In fact, the process is divided into two major parts; the first part groups together the first two blocks 30, 40 and makes it possible to format the meteorological forecasts at the level of the photovoltaic modules of the device whereas the second part consists of a calculation of the projected electrical production of these photovoltaic modules starting precisely from these meteorological forecasts formatted.
  • the last block 60 is in fact an element belonging to each of the three preceding models since it participates in the calculation implemented by these models by defining some of the important parameters of these models.
  • this last block 60 is an integral part of the method, is a part of at least one of the three main calculation models implemented within the three blocks 30, 40, 50, since essential parameters at least one of these models are determined by this last block 60.
  • This invention is suitable for any photovoltaic device, whether it is a large production unit or a small photovoltaic device associated with a device such as a parking meter.
  • the invention finally makes it possible to determine a method for predicting the electrical output of a reliable and accurate photovoltaic installation. It thus allows other applications such as the implementation of a diagnosis of a photovoltaic installation. Indeed, by comparing the actual production with that estimated by the model, it is possible to deduce a measure of the performance of the photovoltaic installation, or even if there is a big difference to diagnose its failure.

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Description

L'invention concerne un procédé de prévision de la production électrique d'un dispositif photovoltaïque. Elle concerne aussi un logiciel de mise en oeuvre d'un tel procédé ainsi qu'un dispositif photovoltaïque mettant en oeuvre un tel procédé. Enfin, elle concerne une utilisation de ce procédé pour le diagnostic d'un dispositif photovoltaïque.The invention relates to a method for predicting the electrical output of a photovoltaic device. It also relates to a software implementation of such a method and a photovoltaic device implementing such a method. Finally, it relates to a use of this method for diagnosing a photovoltaic device.

La part de production d'énergie électrique provenant des installations photovoltaïques augmente rapidement. Une particularité de cette production solaire provient du fait qu'elle est très irrégulière puisqu'elle varie fortement en fonction des conditions météorologiques. Or lorsque ces installations sont connectées à un réseau électrique, ce caractère imprévisible induit une difficulté de gestion du réseau entier, puisqu'il devient difficile de garantir un équilibre entre la production et la demande en énergie. Plus généralement, ce caractère imprévisible de la production électrique est pénalisant pour tout dispositif dont la source d'énergie repose au moins en partie sur l'énergie solaire.The share of power generation from photovoltaic installations is increasing rapidly. A particularity of this solar production comes from the fact that it is very irregular since it varies greatly depending on the weather conditions. However, when these installations are connected to an electricity grid, this unpredictability leads to difficulty in managing the entire network, since it becomes difficult to guarantee a balance between production and energy demand. More generally, this unpredictable nature of electricity generation is penalizing for any device whose energy source is based at least partly on solar energy.

Pour pallier à cet inconvénient, il existe des modèles de prévision de la production électrique des installations photovoltaïques, à partir des prévisions météorologiques. Une telle solution est par exemple explicitée dans le document EP1660917 . Toutefois, la production électrique d'une installation photovoltaïque dépend de nombreux paramètres et il est difficile de mettre au point un modèle très précis. En effet, il est nécessaire d'exploiter les prévisions météorologiques pour en déduire des prévisions très localisées, jusqu'à obtenir une prévision de l'éclairement dans le plan des modules photovoltaïques, pour finalement estimer la production électrique de l'installation sur la base d'un rendement prédéfini. Lors de toutes ces étapes, il existe de nombreuses erreurs et approximations. Les modèles existants donnent finalement des résultats imprécis et insatisfaisants.To overcome this drawback, there are models for forecasting the electrical production of photovoltaic installations, based on weather forecasts. Such a solution is for example explained in the document EP1660917 . However, the electrical output of a photovoltaic installation depends on many parameters and it is difficult to develop a very precise model. Indeed, it is necessary to exploit the meteorological forecasts to deduce very localized forecasts, until a forecast of the illumination in the plane of the photovoltaic modules, to finally estimate the electrical production of the installation on the basis a predefined yield. During all these steps, there are many errors and approximations. Existing models ultimately give imprecise and unsatisfactory results.

Le document " HOW WELL DO PV MODELLING ALGORITHMS REALLY PREDICT PERFORMANCE" de Steve Ransome décrit la modélisation de la production de panneaux photovoltaïques en fonction du temps (nuageux ou couvert), mais il n'enseigne pas de correction du modèle de prévision en fonction de ce paramètre.The document " HOW WELL DO PV MODELING ALGORITHMS REALLY PREDICT PERFORMANCE "by Steve Ransome describes the modeling of photovoltaic panel production as a function of time (cloudy or overcast), but it does not teach a correction of the forecast model according to this parameter.

Ainsi, un objet général de l'invention est de proposer une solution plus précise et fiable de prévision de la production électrique d'un dispositif photovoltaïque.Thus, a general object of the invention is to provide a more accurate and reliable solution for predicting the electrical output of a photovoltaic device.

A cet effet, l'invention repose un procédé de prévision de la production électrique d'un dispositif photovoltaïque comprenant des modules photovoltaïques, comprenant une première partie d'estimation de l'éclairement qui sera reçu dans le plan des modules photovoltaïques et une seconde partie d'estimation de la production électrique du dispositif photovoltaïque, caractérisé en ce qu'il comprend la première étape suivante :

  • détermination si une période passée considérée est ensoleillée ou nuageuse,
    et caractérisé en ce qu'il comprend la seconde étape suivante de mise en oeuvre d'au moins une des deux étapes suivantes :
    • correction de la seconde partie du procédé de prévision de la production électrique à partir de la mesure de la production électrique réelle des modules photovoltaïques sur la période considérée si cette période considérée est ensoleillée ; et/ou
    • correction de la première partie du procédé de prévision de la production électrique à partir de la mesure de la production électrique réelle des modules photovoltaïques sur la période considérée si cette période considérée est nuageuse.
For this purpose, the invention is based on a method for predicting the electrical output of a photovoltaic device comprising photovoltaic modules, comprising a first portion for estimating the illumination that will be received in the plane of the photovoltaic modules and a second part for estimating the electrical output of the photovoltaic device, characterized in that it comprises the following first step:
  • whether a past period considered is sunny or cloudy,
    and characterized in that it comprises the second following step of implementing at least one of the following two steps:
    • correction of the second part of the electricity production forecasting process from the measurement of the actual electricity production of the photovoltaic modules over the period considered if this period is sunny; and or
    • correction of the first part of the electricity production forecasting process from the measurement of the actual electricity production of the photovoltaic modules over the period considered if this period is cloudy.

L'invention porte aussi sur un support informatique comprenant un logiciel apte à mettre en oeuvre le procédé de prévision de la production électrique d'un dispositif photovoltaïque tel que décrit précédemment.The invention also relates to a computer medium comprising software capable of implementing the method for predicting the electrical production of a photovoltaic device as described above.

L'invention porte aussi sur un dispositif photovoltaïque comprenant des modules photovoltaïques, un élément de mesure de leur production électrique réelle, caractérisé en ce qu'il comprend une unité de gestion mettant en oeuvre le procédé de prévision de la production électrique tel que décrit précédemment.The invention also relates to a photovoltaic device comprising photovoltaic modules, an element for measuring their actual electrical production, characterized in that it comprises a management unit implementing the electricity production forecasting method as described above. .

L'invention porte aussi sur l'utilisation du procédé de prévision de la production électrique d'un dispositif photovoltaïque tel que décrit précédemment pour diagnostiquer l'état d'un dispositif photovoltaïque.The invention also relates to the use of the method for predicting the electrical output of a photovoltaic device as described above for diagnosing the state of a photovoltaic device.

L'invention est plus précisément définie par les revendications.The invention is more precisely defined by the claims.

Ces objets, caractéristiques et avantages de la présente invention seront exposés en détail dans la description suivante d'un mode d'exécution particulier fait à titre non-limitatif en relation avec les figures jointes parmi lesquelles :

  • La figure 1 illustre schématiquement un dispositif photovoltaïque selon un mode d'exécution de l'invention.
  • La figure 2 illustre schématiquement les différents blocs du procédé de prévision de la production photovoltaïque selon le mode d'exécution de l'invention.
  • La figure 3 représente les puissances électriques mesurée et prévue sur une journée selon un premier scénario de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 4 représente le rapport entre la puissance électrique mesurée et la puissance électrique théorique par temps clair en fonction du temps selon le premier scénario de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 5 représente la valeur absolue de la dérivée du rapport entre la puissance électrique mesurée et la puissance électrique théorique par temps clair en fonction du temps selon le premier scénario de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 6 représente les puissances électriques mesurée et théorique par temps clair sur une journée selon un second scénario de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 7 représente le rapport entre la puissance électrique mesurée et la puissance électrique théorique par temps clair en fonction du temps selon le second scénario de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 8 représente la valeur absolue de la dérivée du rapport entre la puissance électrique mesurée et la puissance électrique théorique par temps clair en fonction du temps selon le second scénario de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 9 illustre l'éclairement en fonction du temps selon un autre scénario de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 10 illustre la température en fonction du temps selon cet autre scénario de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 11 illustre les productions mesurée et prévue en fonction du temps selon ce scénario de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 12 représente les pertes de la production photovoltaïque en fonction du rapport de la puissance prévue sur la puissance nominale selon le scénario de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 13 illustre les productions mesurée et prévue après correction en fonction du temps selon le scénario de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 14 illustre la production électrique mesurée durant un dernier scénario de journée nuageuse de mise en oeuvre du mode d'exécution de l'invention.
  • La figure 15 représente les éclairements calculés dans le plan des modules photovoltaïques et dans le plan horizontal selon ce scénario nuageux.
  • La figure 16 illustre des éclairements issus des prévisions météorologiques et des éclairements calculés par le procédé du mode d'exécution de l'invention.
  • La figure 17 illustre l'évolution des poids en fonction de l'irradiation prévue apportés à différentes prévisions météorologiques selon le mode d'exécution de l'invention.
These objects, features and advantages of the present invention will be set forth in detail in the following description of a particular embodiment made in a non-limiting manner in relation to the appended figures among which:
  • The figure 1 schematically illustrates a photovoltaic device according to an embodiment of the invention.
  • The figure 2 schematically illustrates the different blocks of the photovoltaic production forecasting method according to the embodiment of the invention.
  • The figure 3 represents the electric power measured and expected on a day according to a first scenario of implementation of the embodiment of the invention.
  • The figure 4 represents the ratio between the measured electrical power and the theoretical electrical power on a clear day as a function of time according to the first scenario of implementation of the embodiment of the invention.
  • The figure 5 represents the absolute value of the derivative of the ratio between the measured electrical power and the theoretical electrical power on a clear day as a function of time according to the first scenario of implementation of the embodiment of the invention.
  • The figure 6 represents the measured and theoretical electrical power on a clear day over a day according to a second scenario of implementation of the embodiment of the invention.
  • The figure 7 represents the ratio between the measured electrical power and the theoretical electrical power on a clear day as a function of time according to the second scenario of implementation of the embodiment of the invention.
  • The figure 8 represents the absolute value of the derivative of the ratio between the measured electrical power and the theoretical electrical power on a clear day as a function of time according to the second scenario of implementation of the embodiment of the invention.
  • The figure 9 illustrates the illumination as a function of time according to another scenario of implementation of the embodiment of the invention.
  • The figure 10 illustrates the temperature as a function of time according to this alternative implementation scenario of the embodiment of the invention.
  • The figure 11 illustrates the productions measured and planned as a function of time according to this scenario of implementation of the embodiment of the invention.
  • The figure 12 represents the losses of the photovoltaic production as a function of the ratio of the expected power to the nominal power according to the scenario of implementation of the embodiment of the invention.
  • The figure 13 illustrates the productions measured and planned after correction as a function of time according to the scenario of implementation of the embodiment of the invention.
  • The figure 14 illustrates the measured electricity production during a last cloudy day scenario of implementation of the embodiment of the invention.
  • The figure 15 represents the calculated illuminations in the plane of the photovoltaic modules and in the horizontal plane according to this cloudy scenario.
  • The figure 16 illustrates illuminations from meteorological forecasts and illuminations calculated by the method of the embodiment of the invention.
  • The figure 17 illustrates the evolution of the weights according to the irradiation provided provided for different weather forecasts according to the embodiment of the invention.

La figure 1 représente schématiquement un dispositif photovoltaïque selon un mode d'exécution de l'invention. Ce dispositif comprend plusieurs modules photovoltaïques 1 reliés au réseau électrique traditionnel 3 par l'intermédiaire d'un onduleur 2. Les modules peuvent bien entendu être reliés à une application autonome par l'intermédiaire d'un convertisseur. Ce dispositif comprend de plus une unité de contrôle ou de gestion 10 reposant sur un calculateur comprenant un logiciel qui met en oeuvre le procédé de prévision de la production électrique qui sera décrit ci-après. L'unité de contrôle 10 reçoit la mesure de la production électrique réelle de l'installation photovoltaïque 1,2 par une liaison 4. D'autre part, cette unité de contrôle 10 reçoit en entrée par un moyen de communication 6 les données de prévisions météorologiques établies par une entité de prévisions météorologiques 5.The figure 1 schematically represents a photovoltaic device according to an embodiment of the invention. This device comprises several photovoltaic modules 1 connected to the traditional electrical network 3 via an inverter 2. The modules can of course be connected to an autonomous application via a converter. This device further comprises a control unit or management 10 based on a computer comprising software that implements the electric power forecasting method which will be described below. The control unit 10 receives the measurement of the actual electricity production of the photovoltaic installation 1, 2 via a link 4. On the other hand, this control unit 10 receives as input by a communication means 6 the forecast data. meteorological conditions established by a meteorological forecasting entity 5.

L'unité de contrôle 10 met donc en oeuvre un procédé de prévision de la production électrique du dispositif photovoltaïque, qui repose sur différents blocs représentés en figure 2. Cette unité de contrôle peut se trouver située sur le site du dispositif photovoltaïque ou éloignée de ce site. Elle peut consister en des moyens de calcul logiciels et/ou matériels (software et/ou hardware), un ou plusieurs moyen(s) de mémorisation pour stocker les informations à traiter et des moyens de communication.The control unit 10 thus implements a method for predicting the electrical production of the photovoltaic device, which is based on various blocks represented in FIG. figure 2 . This control unit can be located on the site of the photovoltaic device or remote from this site. It may consist of software and / or hardware calculation means (software and / or hardware), one or more storage means for storing the information to be processed and communication means.

Le bloc 20 met en oeuvre des prévisions météorologiques. Cette partie préalable est réalisée par une entité météorologique 5 extérieure au dispositif de production photovoltaïque, selon toutes méthodes : l'invention ne porte pas spécifiquement sur ce bloc. Les résultats 25 obtenus par ce bloc 20 sont transmis par le moyen de communication 6 à l'unité de contrôle 10 du dispositif photovoltaïque. Ces données 25, qui comprennent particulièrement l'irradiation ou l'éclairement et la température ambiante, représentent les entrées essentielles du procédé d'estimation de la production électrique qui va être mis en oeuvre par l'unité de gestion 10, et qui repose sur quatre blocs 30, 40, 50, 60 qui vont maintenant être décrits.Block 20 implements weather forecasts. This preliminary part is performed by a meteorological entity 5 external to the photovoltaic production device, according to all methods: the invention does not relate specifically to this block. The results obtained by this block 20 are transmitted by the communication means 6 to the control unit 10 of the photovoltaic device. These data 25, which particularly comprise the irradiation or the illumination and the ambient temperature, represent the essential inputs of the process of estimation of the electrical production which will be implemented by the management unit 10, and which is based on four blocks 30, 40, 50, 60 which will now be described.

Le premier bloc 30 met en oeuvre le calcul de prévisions météorologiques locales plus affinées que celles transmises par l'entité météorologique 5. Pour cela, il utilise des méthodes d'interpolation et/ou de corrélations statistiques et/ou des bases de données d'historiques de prévision et de mesures par des stations météorologiques, afin d'obtenir comme résultat 35 des grandeurs de prévisions météorologiques, comme l'éclairement dans un plan horizontal et la température, avec un pas spatial et temporel plus fin que celui des données météorologiques 25 reçues depuis le bloc 20. En effet, ces prévisions 25 transmises par le bloc 20 le sont en général selon un maillage de plusieurs kilomètres et un pas temporel de plusieurs heures, ce qui est insuffisant à l'échelle d'un site de production photovoltaïque. Les calculs mis en oeuvre dans ce premier bloc 30 reposent donc sur un premier modèle de calcul.The first block 30 implements the calculation of local meteorological forecasts that are more refined than those transmitted by the meteorological entity 5. For this purpose, it uses interpolation methods and / or statistical correlations and / or data bases. historical prediction and meteorological meteorological data to obtain meteorological forecast quantities, such as illumination in a horizontal plane and temperature, with a finer spatial and temporal pitch than that of meteorological data. received from the block 20. In fact, these forecasts 25 transmitted by the block 20 are generally in a mesh of several kilometers and a time step of several hours, which is insufficient at the scale of a photovoltaic production site . The calculations implemented in this first block 30 are therefore based on a first calculation model.

Ensuite, ces résultats 35 de prévisions météorologiques locales sont exploités par un second bloc 40 qui va calculer l'éclairement prévisionnel dans le plan des modules photovoltaïques, à l'aide d'un second modèle de calcul.Next, these local weather forecast results are exploited by a second block 40 which will calculate the projected illumination in the plane of the photovoltaic modules, using a second calculation model.

Les résultats 45 obtenus par le second bloc 40 sont ensuite utilisés par un troisième bloc 50 qui calcule finalement une estimation de la production électrique 55 du dispositif photovoltaïque en fonction de ses performances, qui sont modélisées par un coefficient de pertes, ou par un rendement, qui peut être fonction de la température et de l'éclairage.The results 45 obtained by the second block 40 are then used by a third block 50 which finally calculates an estimate of the electrical production 55 of the photovoltaic device according to its performances, which are modeled by a coefficient of losses, or by a yield, which can be a function of the temperature and the lighting.

Tous les blocs précédents reposent initialement sur des approches théoriques et/ou empiriques diverses, pouvant appartenir à l'état de la technique. Les résultats 35, 45, 55 obtenus à chaque étape présentent une certaine erreur et incertitude. Selon un élément essentiel de l'invention, au moins un des trois modèles, préférentiellement les trois, mis en oeuvre par respectivement les blocs 30, 40, 50 est amélioré à partir de la comparaison directe ou indirecte entre la mesure de la production électrique réelle et la valeur de la production estimée sur une période donnée, et en fonction de la situation ensoleillée ou non de cette même période.All the preceding blocks are initially based on various theoretical and / or empirical approaches that may belong to the state of the art. The results 35, 45, 55 obtained at each step show some error and uncertainty. According to an essential element of the invention, at least one of the three models, preferably all three, implemented by the blocks 30, 40, 50, respectively, is improved from the direct or indirect comparison between the measurement of the actual electricity production. and the value of production estimated over a given period, and according to the sunny situation or not of the same period.

Pour cela, un dernier bloc 60 du procédé d'estimation de la production électrique transmet des données 63, 64, 65 aux blocs 30, 40 et 50 pour améliorer les modèles mis en oeuvre dans ces blocs selon un mécanisme empirique d'apprentissage. Selon le principe de l'invention, cet apprentissage dépend de deux étapes essentielles :

  • E1 - la détermination si la journée considérée est ensoleillée ou non ;
  • E2 - la correction d'une partie du procédé d'estimation de la production électrique, cette partie étant déterminée en fonction du résultat de l'étape E1, la correction reposant sur la comparaison entre la mesure directe ou indirecte d'une grandeur, cette grandeur étant directement mesurée s'il s'agit de la production électrique ou indirectement déduite de cette production électrique mesurée dans les autres cas, et l'estimation de cette même grandeur obtenue par le procédé mis en oeuvre dans l'unité de gestion 10 du dispositif.
For this, a last block 60 of the electric power estimation method transmits data 63, 64, 65 to blocks 30, 40 and 50 to improve the models implemented in these blocks according to an empirical learning mechanism. According to the principle of the invention, this learning depends on two essential steps:
  • E1 - whether the day is sunny or not;
  • E2 - the correction of a part of the process of estimating the electrical production, this part being determined according to the result of the step E1, the correction being based on the comparison between the direct or indirect measurement of a quantity, this magnitude being directly measured if it is the electrical production or indirectly deduced from this electrical production measured in other cases, and the estimate of this same quantity obtained by the process implemented in the management unit 10 of the device.

Le bloc 60 met donc en oeuvre une première étape E1 essentielle de l'invention qui consiste à déterminer si une journée passée considérée est ensoleillée ou non. Le concept de l'invention consiste à considérer que si la journée est ensoleillée, les résultats obtenus par les blocs 30 et 40 du procédé de l'invention sont corrects, c'est-à-dire que l'éclairement estimé dans le plan des modules photovoltaïques est juste. L'erreur constatée sur la valeur de la prévision de la production électrique par le procédé, par sa comparaison avec la valeur réelle telle que mesurée, est alors uniquement causée par l'imprécision du troisième modèle de calcul mis en oeuvre au niveau du troisième bloc 50. Cette approche revient à considérer que par temps ensoleillé, l'erreur commise par les deux premiers blocs 30, 40 est négligeable par rapport à celle commise par le troisième bloc 50. Au contraire, si la journée n'est pas ensoleillée, nous la qualifierons simplement de « nuageuse » pour des raisons de simplification de la description, l'erreur finale constatée entre la prévision de la production électrique et la mesure réelle de cette production est attribuée aux deux premiers blocs 20, 30 ou à l'un d'entre eux, l'erreur engendrée par le troisième bloc 50 étant alors considérée comme négligeable.Block 60 thus implements an essential first step E1 of the invention which consists in determining whether a past day considered is sunny or not. The concept of the invention is to consider that if the day is sunny, the results obtained by the blocks 30 and 40 of the method of the invention are correct, that is to say that the estimated illumination in the plane of photovoltaic modules is right. The error noted on the value of the forecast of the electrical production by the method, by its comparison with the real value as measured, is then only caused by the inaccuracy of the third calculation model implemented at the level of the third block 50. This approach amounts to considering that in sunny weather, the error committed by the first two blocks 30, 40 is negligible compared to that made by the third block 50. On the contrary, if the day is not sunny, we simply call it "cloudy" for the sake of simplification of the description, the final error found between the forecast of electricity production and the actual measurement of this production is attributed to the first two blocks 20, 30 or to one of between them, the error generated by the third block 50 then being considered negligible.

Ce concept d'apprentissage présente l'avantage de permettre l'amélioration empirique des modèles de calcul mis en oeuvre par le procédé à partir de la seule mesure de la production réelle obtenue pour le dispositif photovoltaïque. Il ne nécessite pas plusieurs mesures différentes pour le traitement séparé des divers blocs du procédé, et par exemple ne nécessite pas de capteur d'ensoleillement comme un pyranomètre, qui est relativement coûteux.This learning concept has the advantage of allowing the empirical improvement of the calculation models implemented by the method from the sole measurement of the actual production obtained for the photovoltaic device. It does not require several different measures for the separate treatment of the various process blocks, and for example does not require a sunshine sensor such as a pyranometer, which is relatively expensive.

La première étape E1 de détermination du type de journée, ensoleillée ou nuageuse, va maintenant être décrite. Le principe de cette détermination repose sur la comparaison entre d'une part la production d'électricité mesurée, reposant sur une série de mesures E11 par exemple avec une périodicité comprise entre 1 seconde et 10 minutes, et la même série obtenue pour la production d'électricité théorique par temps clair, en faisant l'hypothèse de temps clair, de préférence selon une fréquence en phase avec la série de mesures. Pour obtenir cette série de valeurs de production électrique théorique par temps clair, une première sous-étape consiste à déterminer la série de prévision de l'éclairement E12 dans le plan des modules photovoltaïques par temps clair par tout modèle existant, par exemple avec celui mis en oeuvre dans l'unité de gestion 10. Cette série peut aussi être corrigée à partir de prévisions météorologiques. D'autre part, une série de températures ambiantes est établie E13, soit par mesure, soit par calcul à l'aide de modèles, soit à partir des prévisions météorologiques. Enfin, la production photovoltaïque par temps clair E14 est alors calculée avec le bloc 50 du procédé de l'unité de gestion 10 du dispositif photovoltaïque, à partir de ces séries de valeurs d'éclairement et de température, en tenant compte des pertes ou performances au niveau des modules photovoltaïques telles qu'évaluées par le modèle mis en oeuvre au niveau de l'unité de gestion 10.The first step E1 of determining the type of day, sunny or cloudy, will now be described. The principle of this determination is based on a comparison between electricity production on the one hand measured, based on a series of measurements E11 for example with a periodicity of between 1 second and 10 minutes, and the same series obtained for the theoretical electricity production on a clear day, making the assumption of clear weather, preferably according to a frequency in phase with the series of measurements. In order to obtain this series of values of theoretical electricity production on a clear day, a first sub-step consists of determining the E12 illumination forecast series in the plane of the photovoltaic modules on a clear day by any existing model, for example with that set implemented in the management unit 10. This series can also be corrected from weather forecasts. On the other hand, a series of ambient temperatures is established E13, either by measurement, or by calculation using models, or from weather forecasts. Finally, the photovoltaic production in clear weather E14 is then calculated with block 50 of the process of the management unit 10 of the photovoltaic device, from these series of values of illumination and temperature, taking into account the losses or performances. at the level of the photovoltaic modules as evaluated by the model implemented at the level of the management unit 10.

Lorsque les deux séries à comparer sont obtenues, il reste finalement à déterminer si la journée doit être considérée comme ensoleillée ou nuageuse. Cette qualification est mise en oeuvre par la détection d'éventuels passages nuageux, ce qui est aisément détectable puisque l'éclairement, et par conséquent la production électrique, baisse alors d'environ 80%. La journée ne sera pas considérée comme nuageuse s'il n'y a qu'un seul court passage nuageux. Un seuil prédéfini permet de fixer une limite entre une journée qui sera considérée comme une journée ensoleillée et une journée nuageuse. Cette dernière étape de qualification est compliquée par le fait qu'une zone d'ombre sur les modules photovoltaïques peut être provoquée par l'environnement du dispositif photovoltaïque, comme un bâtiment faisant de l'ombre à une certaine heure, et non par un passage nuageux. Le procédé fait donc la distinction entre le passage d'un nuage et un tel ombrage. Pour cela, le procédé de définition du type de journée repose non seulement sur l'analyse du rapport entre la puissance électrique mesurée et la puissance électrique théorique par temps clair E15, mais aussi sur l'analyse de la dérivée de ce rapport E16, pour tenir compte de la vitesse de variation de ce rapport. Deux séries temporelles sont donc obtenues, à partir desquelles on détecte des événements anomaux, définis par un certain seuil prédéfini. Dès que la quantité d'événements anormaux dépasse un certain seuil E17, la journée est considérée comme non ensoleillée, et sinon elle est ensoleillée.When the two series to be compared are obtained, it remains to be determined whether the day should be considered sunny or cloudy. This qualification is implemented by the detection of possible cloudy passages, which is easily detectable since the illumination, and therefore the power output, then decreases by about 80%. The day will not be considered cloudy if there is only one short cloudy passage. A predefined threshold sets a limit between a day that will be considered a sunny day and a cloudy day. This last stage of qualification is complicated by the fact that a shadow zone on the photovoltaic modules can be caused by the environment of the device photovoltaic, like a building shading at a certain time, and not a cloudy passage. The method therefore distinguishes between the passage of a cloud and such shading. For this, the method of defining the type of day is based not only on the analysis of the ratio between the measured electrical power and the theoretical electrical power on a clear day E15, but also on the analysis of the derivative of this ratio E16, for take into account the speed of variation of this ratio. Two time series are thus obtained, from which anomalous events are detected, defined by a certain predefined threshold. As soon as the amount of abnormal events exceeds a certain threshold E17, the day is considered as not sunny, and otherwise it is sunny.

En résumé, la première étape E1 de détermination du type de journée, ensoleillée ou nuageuse, comprend les sous-étapes suivantes :

  • E11 - Mesure selon une fréquence prédéfinie de la production d'électricité réelle ;
  • E14 - Détermination de la production d'électricité théorique par temps clair à partir d'une estimation de l'éclairement dans le plan des modules photovoltaïques par temps clair E12 et à partir de l'établissement d'une série de températures ambiantes E13 ;
  • E15 - analyse du rapport entre la puissance électrique mesurée et la puissance électrique théorique avec l'hypothèse de temps clair, en détectant d'éventuels événements anormaux ;
  • E16 - analyse de la dérivée de ce rapport, en détectant d'éventuels événements anormaux ;
  • E17 - détermination du type de journée, en comparant la quantité d'événements anormaux détectés par rapport à un seuil prédéfini.
In summary, the first step E1 of determining the type of day, sunny or cloudy, comprises the following substeps:
  • E11 - Measurement according to a predefined frequency of real electricity production;
  • E14 - Determination of the theoretical electricity production on a clear day from an estimate of the illumination in the plane of the photovoltaic modules in clear weather E12 and from the establishment of a series of ambient temperatures E13;
  • E15 - analysis of the ratio between the measured electrical power and the theoretical electrical power with the hypothesis of clear weather, by detecting any abnormal events;
  • E16 - analysis of the derivative of this report, detecting any abnormal events;
  • E17 - determination of the type of day, comparing the amount of abnormal events detected with a predefined threshold.

En variante, le procédé précédent peut être simplifié en ne mettant en oeuvre qu'une seule des deux étapes d'analyse E15, E16. De plus, le procédé pourrait comprendre une étape préalable de détection des masques, c'est-à-dire des obstacles naturels comme les montagnes, les bâtiments,..., qui créent des ombrages au niveau des modules photovoltaïques, au moins à certaines périodes de l'année.In a variant, the preceding method can be simplified by implementing only one of the two analysis steps E15, E16. In addition, the method could include a preliminary stage of detection of masks, that is to say natural obstacles such as mountains, buildings, ..., which create shading at the photovoltaic modules, at least some periods of the year.

Les figures 3 à 5 illustrent un premier exemple de mise en oeuvre de l'étape E1 décrite précédemment. La figure 3 représente deux courbes 70, 71 correspondant respectivement aux puissances électriques mesurée et théorique par temps clair sur une journée selon un premier scénario. La figure 4 représente le rapport 72 entre la puissance électrique mesurée sur la puissance électrique théorique par temps clair en fonction du temps pour ce scénario. Sur cette figure, une zone rectangulaire 73 correspond à un seuil au delà duquel l'événement est considéré anormal. Lorsque la courbe 72 reste dans ce domaine 73, la situation correspond à une situation ensoleillée. Selon ce mode d'exécution, le domaine 73 dit de « journée ensoleillée » est défini pour une valeur du rapport de puissance 72 comprise entre 0,5 et 1. Enfin, la figure 5 illustre la courbe 74 de la valeur absolue de la dérivée du rapport de puissance en fonction du temps. De même, une zone rectangulaire 75 définie par une valeur de ce rapport comprise entre 0 et 0,1 correspond à une situation de journée ensoleillée. Finalement, il ressort que les deux courbes 72, 74 du rapport de puissance mesurée sur la puissance théorique par temps clair et de la valeur absolue de sa dérivée sortent très rarement des zones ensoleillées 73, 75. La journée considérée par ce scénario est donc considérée comme une journée ensoleillée.The Figures 3 to 5 illustrate a first example of implementation of step E1 described above. The figure 3 represents two curves 70, 71 respectively corresponding to the measured and theoretical electrical power on a clear day on a day according to a first scenario. The figure 4 represents the ratio 72 between the electric power measured on the theoretical electrical power on a clear day as a function of time for this scenario. In this figure, a rectangular zone 73 corresponds to a threshold beyond which the event is considered abnormal. When the curve 72 remains in this area 73, the situation corresponds to a sunny situation. According to this embodiment, the domain 73 called "sunny day" is defined for a value of the power ratio 72 between 0.5 and 1. Finally, the figure 5 illustrates the curve 74 of the absolute value of the derivative of the power ratio as a function of time. Similarly, a rectangular zone 75 defined by a value of this ratio between 0 and 0.1 corresponds to a sunny day situation. Finally, it appears that the two curves 72, 74 of the power ratio measured on the theoretical power on a clear day and the absolute value of its derivative very rarely leave the sunny areas 73, 75. The day considered by this scenario is therefore considered like a sunny day.

Les figures 6 à 8 illustrent un second exemple de mise en oeuvre de l'étape E1 décrite précédemment. La figure 6 représente deux courbes 70', 71' correspondant respectivement aux puissances électriques mesurée et théorique par temps clair selon un second scénario d'une journée. La figure 7 représente en fonction du temps le rapport 72' entre la puissance électrique mesurée sur la puissance électrique théorique par temps clair pour ce scénario. Sur cette figure, la zone rectangulaire 73' correspond à une situation ensoleillée, pour une valeur du rapport de puissance 72' comprise entre 0,5 et 1. Enfin, la figure 8 illustre la courbe 74' de la valeur absolue de la dérivée du rapport de puissance en fonction du temps. De même, la zone rectangulaire 75' définie par une valeur comprise entre 0 et 0,1 de la valeur absolue de cette dérivée correspond à une situation de journée ensoleillée. Finalement, il ressort que les deux courbes 72', 74' du rapport de puissance mesurée sur la puissance théorique par temps clair et de la valeur absolue de sa dérivée sortent très souvent des zones ensoleillées 73', 75'. La journée considérée par ce scénario est donc considérée comme une journée nuageuse.The Figures 6 to 8 illustrate a second example of implementation of step E1 described above. The figure 6 represents two curves 70 ', 71' respectively corresponding to the electrical power measured and theoretical on a clear day according to a second scenario of one day. The figure 7 represents as a function of time the ratio 72 'between the electric power measured on the theoretical electrical power on a clear day for this scenario. In this figure, the rectangular zone 73 'corresponds to a sunny situation, for a value of the power ratio 72' of between 0.5 and 1. Finally, the figure 8 illustrates the curve 74 'of the absolute value of the derivative of the power ratio as a function of time. Similarly, the rectangular zone 75 'defined by a value between 0 and 0.1 of the absolute value of this derivative corresponds to a sunny day situation. Finally, it appears that the two curves 72 ', 74' of the power ratio measured on the theoretical power on a clear day and the absolute value of its derivative very often leave sunny areas 73 ', 75'. The day considered by this scenario is therefore considered a cloudy day.

Ensuite, le procédé de prévision de la production électrique du dispositif photovoltaïque met en oeuvre une seconde étape E2 qui distingue deux situations en fonction du résultat de la première étape E1.Next, the method for predicting the electrical output of the photovoltaic device implements a second step E2 which distinguishes two situations as a function of the result of the first step E1.

D'abord, si la journée est ensoleillée et que l'entité de prévisions météorologiques l'avait prévu, il est considéré que la première partie du calcul du procédé mise en oeuvre par les deux premiers blocs 30, 40 est correcte, c'est-à-dire que l'éclairement prévu dans le plan des modules photovoltaïques présente un résultat satisfaisant, dont l'erreur est négligeable. Cet éclairement est donc considéré comme l'éclairement réel, équivalent à celui qui serait obtenu à partir d'une mesure. Ainsi, dans une telle situation, l'erreur constatée entre la production d'électricité réelle mesurée et celle qui était prévue par le procédé dépend uniquement du troisième modèle de calcul mis en oeuvre par le troisième bloc 50 du procédé. Ce calcul consiste à déterminer la production du dispositif photovoltaïque en fonction de l'éclairement, en tenant compte de pertes de puissance en fonction de la température. L'erreur constatée est utilisée pour corriger ce troisième modèle de calcul, en corrigeant le coefficient de pertes utilisé dans ce troisième modèle. Cette correction peut se faire chaque jour ensoleillé, en modifiant immédiatement le coefficient de pertes du modèle afin de le réutiliser immédiatement pour les futures mises en oeuvre du procédé. En variante, le coefficient de pertes recalculé peut être stocké dans une mémoire de l'unité de gestion 10, et servir de base à un recalcul périodique d'un nouveau coefficient de pertes à partir de ces valeurs stockées, comme une simple moyenne de ces valeurs par exemple. La nouvelle valeur du coefficient de pertes remplace alors la précédente pour les futurs calculs de prévision de la production électrique. Ainsi, l'enseignement des journées ensoleillées permet l'apprentissage du troisième modèle utilisé dans le procédé de prévision de la production électrique, les autres modèles de calcul mis en oeuvre dans ce procédé restant inchangés durant ces périodes de journées ensoleillées.First, if the day is sunny and the meteorological forecasting entity had planned, it is considered that the first part of the calculation of the process implemented by the first two blocks 30, 40 is correct, it is that is, the illumination provided in the plane of the photovoltaic modules has a satisfactory result, the error of which is negligible. This illumination is therefore considered as actual illumination, equivalent to that which would be obtained from a measurement. Thus, in such a situation, the error found between the actual measured electricity production and that predicted by the process depends solely on the third calculation model implemented by the third block 50 of the process. This calculation consists in determining the production of the photovoltaic device as a function of the illumination, taking into account power losses as a function of temperature. The error observed is used to correct this third model of calculation, by correcting the coefficient of losses used in this third model. This correction can be done every sunny day, by immediately modifying the coefficient of losses of the model in order to reuse it immediately for the future implementations of the process. Alternatively, the recalculated loss coefficient can be stored in a memory of the management unit 10, and serve as a basis for a periodic recalculation of a new loss coefficient from these stored values, as a simple average of these values for example. The new value of the loss coefficient then replaces the previous value for future calculations of electricity production forecasts. Thus, teaching sunny days allows the learning of the third model used in the electricity production forecasting process, the other calculation models implemented in this process remaining unchanged during these periods of sunny days.

Les figures 9 à 13 illustrent un exemple de mise en oeuvre de cette seconde étape E2 dans le cas d'une journée ensoleillée. Les figures 9 et 10 illustrent respectivement les courbes 76 et 77 d'éclairement et de température obtenues en fonction du temps selon le scénario choisi. La figure 11 illustre les courbes de production mesurée 78 et de production prévue 79 en fonction du temps au cours de cette journée. L'écart entre les deux courbes précédentes permet de déterminer les pertes en fonction du rapport de la puissance prévue sur la puissance nominale, qui sont représentées par les courbes 80 sur la figure 12. Ces pertes sont modélisées par un polynôme représenté par la courbe 81 de cette même figure. Ces pertes ainsi obtenues et modélisées permettent de modifier le coefficient de pertes du troisième modèle de calcul du procédé de provision de l'invention. En utilisant ce nouveau coefficient pour ce scénario, on obtient une nouvelle courbe 82 de production prévue, beaucoup plus proche que la courbe initiale 79 de la courbe de production mesurée 78, comme cela est illustré sur la figure 13.The Figures 9 to 13 illustrate an example of implementation of this second step E2 in the case of a sunny day. The Figures 9 and 10 respectively illustrate the curves 76 and 77 of illumination and temperature obtained as a function of time according to the chosen scenario. The figure 11 illustrates the measured production and expected production curves 79 as a function of time during that day. The difference between the two preceding curves makes it possible to determine the losses as a function of the ratio of the expected power to the nominal power, which are represented by the curves 80 on the figure 12 . These losses are modeled by a polynomial represented by the curve 81 of this same figure. These losses thus obtained and modeled make it possible to modify the coefficient of losses of the third model of calculation of the method of provision of the invention. Using this new coefficient for this scenario, a new expected production curve 82 is obtained, much closer than the initial curve 79 of the measured production curve 78, as illustrated in FIG. figure 13 .

Si la journée est nuageuse, il est considéré que le troisième modèle de calcul du procédé est correct, c'est-à-dire que la production électrique calculée en fonction de l'éclairement dans le plan des modules photovoltaïques présente un résultat satisfaisant, dont l'erreur est négligeable. Ainsi, dans une telle situation, l'erreur constatée entre la production d'électricité réelle mesurée et celle qui est estimée par le procédé dépend uniquement des deux premiers modèles de calcul mis en oeuvre par le procédé, tels que décrits en référence avec au moins un des deux premiers blocs 30, 40. La production électrique réelle est mesurée puis en appliquant un calcul inverse du calcul mis en oeuvre dans le troisième bloc 50, on en déduit une « mesure virtuelle ou indirecte », soit une valeur réelle indirecte, de l'éclairement qui est reçu par les modules photovoltaïques. La première partie du modèle incluant les deux premiers modèles de calcul mis en oeuvre au sein des blocs 30 et 40 permet d'autre part de calculer un éclairement estimé à partir des prévisions météorologiques. Ces éclairements mesurés et estimés sont comparés et leur différence sert de point de départ à une correction d'au moins un des deux modèles de calcul des deux premiers blocs 30, 40 du procédé. Cette correction peut consister en différentes solutions. D'abord, elle peut ne porter que sur un des deux modèles de calcul mis en oeuvre ou sur les deux. Ensuite, elle peut reposer sur un calcul de corrélations entre la prévision météorologique et l'éclairement local, par une approche statistique ou par réseaux de neurones.If the day is cloudy, it is considered that the third model of calculation of the process is correct, that is to say that the electrical production calculated according to the illumination in the plane of the photovoltaic modules presents a satisfactory result, of which the error is negligible. Thus, in such a situation, the error observed between the actual measured electricity production and that estimated by the method depends solely on the first two calculation models implemented by the method, as described with reference to at least one of the first two blocks 30, 40. The actual electrical production is measured then by applying a calculation inverse to the calculation implemented in the third block 50, a "virtual or indirect measure", ie an indirect real value, of the illumination that is received by the photovoltaic modules. The first part of the model including the first two calculation models implemented in the blocks 30 and 40 allows on the other hand to calculate an estimated illumination from the weather forecasts. These measured and estimated illuminances are compared and their difference serves as a starting point for a correction of at least one of the two calculation models of the first two blocks 30, 40 of the method. This correction can consist of different solutions. First, it can relate to only one of the two calculation models implemented or both. Then, it can be based on a computation of correlations between weather forecasting and local illumination, by a statistical approach or by neural networks.

Selon une variante de mise en oeuvre de cette seconde étape E2 dans une situation de journée nuageuse, le second modèle de calcul mis en oeuvre dans le second bloc 40 du procédé est considéré comme fiable. L'étape de correction consiste alors à améliorer uniquement le premier modèle de calcul mis en oeuvre dans le premier bloc 30 du procédé, qui consiste en une extrapolation des données météorologiques afin d'obtenir une estimation de l'éclairement dans un plan horizontal. L'éclairement réel dans un plan horizontal est virtuellement connu, par un calcul inverse du second modèle de calcul à partir de l'éclairement dans le plan des modules photovoltaïques qui est déduit de la mesure de la production électrique réelle, comme cela a été explicité ci-dessus. Il s'agit donc d'un éclairement qu'on peut qualifier de mesure virtuelle, puisqu'il est indirectement mesuré par la mesure de la production électrique réelle. Ensuite, la comparaison entre cet éclairement virtuel mesuré et celui estimé par le procédé sert de base à l'amélioration du premier modèle de calcul du procédé.According to an alternative embodiment of this second step E2 in a cloudy day situation, the second calculation model implemented in the second block 40 of the method is considered reliable. The correction step then consists in improving only the first calculation model implemented in the first block 30 of the method, which consists of an extrapolation of the meteorological data in order to obtain an estimate of the illumination in a horizontal plane. The actual illumination in a horizontal plane is virtually known, by an inverse calculation of the second model of computation from the illumination in the plane of the photovoltaic modules which is deduced from the measurement of the real electrical production, as has been made explicit. above. It is therefore an illumination that can be described as a virtual measure, since it is indirectly measured by the measurement of real electricity production. Then, the comparison between this virtual illuminance measured and that estimated by the process serves as a basis for improving the first calculation model of the process.

Les figures 14 à 17 illustrent un exemple de mise en oeuvre de cette seconde étape E2 dans le cas d'une journée nuageuse. La figure 14 illustre la courbe 83 de la production électrique mesurée durant la journée nuageuse. La figure 15 montre respectivement les courbes 84 et 85 d'éclairements dans le plan des modules photovoltaïques et dans le plan horizontal en fonction du temps selon le scénario choisi. La figure 16 illustre des points 86 représentant les éclairements en fonction du temps issus des prévisions météorologiques en quatre points autour du dispositif de production photovoltaïque, alors que les points 87 représentent ces mêmes éclairements virtuellement mesurés. Il a été choisi ici de sélectionner les quatre points de données météorologiques qui sont les plus proches du site de production. Il est ensuite possible d'en déduire l'éclairement sur le site par exemple en appliquant une pondération de chacun des quatre points obtenus par les données météorologiques. Les poids correspondants sont déterminés et améliorés en fonction de la base de données de mesures réalisées par temps nuageux. Ils peuvent être calculés par des méthodes purement statistiques, par de l'intelligence artificielle, etc...Cette base de données sert à recalculer les poids pour obtenir un résultat plus précis. Ainsi, la figure 17 illustre l'évolution pendant plusieurs mois des quatre poids considérés en fonction de l'irradiation prévue dans les quatre points considérés.The Figures 14 to 17 illustrate an example of implementation of this second step E2 in the case of a cloudy day. The figure 14 illustrates the curve 83 of the electricity production measured during the cloudy day. The figure 15 shows respectively the curves 84 and 85 of the illuminations in the plane of the photovoltaic modules and in the horizontal plane as a function of time according to the chosen scenario. The figure 16 illustrates points 86 representing the illumination as a function of time resulting from the four-point weather forecast around the photovoltaic production device, while the points 87 represent these same virtually measured illuminations. It was chosen here to select the four meteorological data points that are closest to the production site. It is then possible to deduce the illumination on the site for example by applying a weighting of each of the four points obtained by the meteorological data. The corresponding weights are determined and improved according to the database of measurements made in cloudy weather. They can be calculated by purely statistical methods, by artificial intelligence, etc. This database is used to recalculate the weights to obtain a more precise result. So, the figure 17 illustrates the evolution over several months of the four weights considered according to the irradiation envisaged in the four points considered.

Le mécanisme d'apprentissage a été décrit sur la base d'un découpage temporel à l'échelle d'une journée. Toutefois, tout autre découpage temporel serait envisageable. Par exemple, il est possible de suivre le même principe sur la base d'une demi-journée, en déterminant d'abord si cette demi-journée est ensoleillée ou nuageuse, puis en poursuivant le reste du procédé. D'autre part, le mécanisme d'apprentissage peut être mis en oeuvre sur toutes ces périodes, ou sur une partie seulement de ces périodes en fonction de critères prédéfinis, comme uniquement les périodes pour lesquelles des mesures de la production électrique du dispositif photovoltaïque sont disponibles avec une fréquence suffisante. De plus, il peut être choisi de ne mettre en oeuvre ce mécanisme d'apprentissage que sur une durée limitée, prédéfinie, ou ce mécanisme peut être mis en oeuvre de manière permanente, illimitée.The learning mechanism has been described on the basis of a time division at the scale of one day. However, any other temporal division would be possible. For example, it is possible to follow the same principle on the basis of half a day, first determining whether this half-day is sunny or cloudy, then continuing the rest of the process. On the other hand, the learning mechanism can be implemented over all these periods, or only a part of these periods according to predefined criteria, such as only the periods for which measurements of the electrical production of the photovoltaic device are available with sufficient frequency. In addition, it can be chosen to implement this learning mechanism for a limited time, predefined, or this mechanism can be implemented permanently, unlimited.

L'invention permet de préférence d'améliorer les trois modèles de calcul principaux du procédé, mis en oeuvre au sein des trois blocs 30, 40, 50. Toutefois, son utilisation pour un seul quelconque de ces trois blocs permet déjà une amélioration des procédés existants et n'échappe pas au concept de la présente invention.The invention preferably makes it possible to improve the three main calculation models of the method, implemented within the three blocks 30, 40, 50. However, its use for any one of these three blocks already makes it possible to improve the processes existing and does not escape the concept of the present invention.

D'autre part, l'invention est avantageuse en ce qu'elle permet d'aboutir à un procédé de prévision de la production électrique amélioré à l'aide de la seule mesure de la production électrique réelle. Toutefois, ce concept de l'invention peut être combiné avec tout autre système de correction empirique des modèles de calcul, mis en oeuvre sur la base d'autres mesures par exemple, sans sortir du concept de l'invention.On the other hand, the invention is advantageous in that it leads to a method for predicting the improved electrical output using the only measurement of actual electricity production. However, this concept of the invention can be combined with any other empirical correction system calculation models, implemented on the basis of other measurements for example, without departing from the concept of the invention.

De plus, l'invention a été décrite en utilisant certaines grandeurs importantes comme l'éclairement, qui représente une puissance reçue par unité de surface. En variante, d'autres grandeurs voisines permettent de mettre en oeuvre les mêmes calculs et le même procédé, comme par exemple l'irradiation, qui représente l'énergie reçue par unité de surface. Il est possible de passer de l'éclairement à l'irradiation par une simple conversion et l'utilisation de l'une ou l'autre de ces grandeurs dans le procédé représente des solutions équivalentes.In addition, the invention has been described using certain important quantities such as illumination, which represents a received power per unit area. As a variant, other neighboring quantities make it possible to implement the same calculations and the same method, such as, for example, irradiation, which represents the energy received per unit area. It is possible to switch from irradiance to irradiation by simple conversion and the use of one or other of these magnitudes in the process represents equivalent solutions.

Le procédé de l'invention a été présenté selon un découpage abstrait en différents blocs 30, 40, 50, 60 pour faciliter sa compréhension. Toutefois, il représente un tout indissociable dont les différents éléments peuvent être imbriqués de manière plus complexe. En fait, le procédé se découpe en deux grandes parties principales ; la première partie regroupe les deux premiers blocs 30, 40 et permet de formater les prévisions météorologiques au niveau des modules photovoltaïques du dispositif alors que la seconde partie consiste en un calcul de la production électrique prévisionnelle de ces modules photovoltaïques à partir précisément de ces prévisions météorologiques formatées. Le dernier bloc 60 est en fait un élément appartenant à chacun des trois modèles précédents puisqu'il participe au calcul mis en oeuvre par ces modèles en définissant certains des paramètres importants de ces modèles. Par ce biais, quels que soient les modèles de calcul initiaux servant de point de départ du procédé, des modèles théoriques et/ou empiriques, existants ou non dans l'état de la technique, ces modèles, par leur combinaison avec les étapes mises en oeuvre par le bloc 60 de l'invention deviennent des modèles différents, nouveaux et plus performants. La partie essentielle du procédé décrit précédemment est donc celle mise en oeuvre dans le dernier bloc 60. Cette partie du procédé a été présentée pour des raisons de simplification de la description comme une partie distincte du procédé, mais selon une vision plus juste, comme cela a été explicité ci-dessus, ce dernier bloc 60 est une partie intégrante du procédé, est une partie d'au moins un des trois modèles de calcul principaux mis en oeuvre au sein des trois blocs 30, 40, 50, puisque des paramètres essentiels d'au moins un de ces modèles sont déterminés par ce dernier bloc 60.The method of the invention has been presented according to an abstract division into different blocks 30, 40, 50, 60 to facilitate its understanding. However, it represents an indissociable whole whose different elements can be nested in a more complex way. In fact, the process is divided into two major parts; the first part groups together the first two blocks 30, 40 and makes it possible to format the meteorological forecasts at the level of the photovoltaic modules of the device whereas the second part consists of a calculation of the projected electrical production of these photovoltaic modules starting precisely from these meteorological forecasts formatted. The last block 60 is in fact an element belonging to each of the three preceding models since it participates in the calculation implemented by these models by defining some of the important parameters of these models. In this way, whatever the initial calculation models serving as point of process, theoretical and / or empirical models, existing or not in the state of the art, these models, by their combination with the steps implemented by the block 60 of the invention become different models, new and more efficient. The essential part of the process described above is therefore that implemented in the last block 60. This part of the process has been presented for reasons of simplification of the description as a separate part of the process, but according to a more accurate view, as this has been explained above, this last block 60 is an integral part of the method, is a part of at least one of the three main calculation models implemented within the three blocks 30, 40, 50, since essential parameters at least one of these models are determined by this last block 60.

Cette invention est adaptée à tout dispositif photovoltaïque, qu'il s'agisse d'une grande unité de production ou d'un petit dispositif photovoltaïque associé à un appareil comme un parcmètre.This invention is suitable for any photovoltaic device, whether it is a large production unit or a small photovoltaic device associated with a device such as a parking meter.

De plus, l'invention permet finalement de déterminer un procédé de prévision de la production électrique d'une installation photovoltaïque fiable et précis. Il permet ainsi d'autres applications comme la mise en oeuvre d'un diagnostic d'une installation photovoltaïque. En effet, en comparant la production réelle avec celle estimée par le modèle, il est possible d'en déduire une mesure de la performance de l'installation photovoltaïque, voire en cas de forte différence de diagnostiquer sa défaillance.In addition, the invention finally makes it possible to determine a method for predicting the electrical output of a reliable and accurate photovoltaic installation. It thus allows other applications such as the implementation of a diagnosis of a photovoltaic installation. Indeed, by comparing the actual production with that estimated by the model, it is possible to deduce a measure of the performance of the photovoltaic installation, or even if there is a big difference to diagnose its failure.

Claims (15)

  1. Method of forecasting the electrical production of a photovoltaic device comprising photovoltaic modules (1), comprising a first part of estimating the lighting that will be received in the plane of the photovoltaic modules (1) and a second part of estimating the electrical production of the photovoltaic device, characterized in that it comprises the following first step:
    (E1) - determination of whether a past considered period is sunny or cloudy,
    and characterized in that it comprises the following second step (E2) of implementing at least one of the following two steps:
    (E2) - correction of the second part of the method of forecasting the electrical production based on the measurement of the true electrical production of the photovoltaic modules over the past considered period if this past considered period is sunny; and/or
    - correction of the first part of the method of forecasting the electrical production based on the measurement of the true electrical production of the photovoltaic modules over the past considered period if this past considered period is cloudy.
  2. Method of forecasting the electrical production of a photovoltaic device according to the previous claim, characterized in that the first step (E1) for determining whether a past considered period is sunny or cloudy comprises the following substeps:
    (E11) - measurement according to a predefined frequency during the considered period of the true electricity production;
    (E14) - determination of the theoretical electricity production assuming clear weather;
    (E15) - analysis of the ratio between the measured electrical power and the theoretical electrical power assuming clear weather, by detecting any abnormal events and/or (E16) analysis of the derivative in this ratio, by detecting any abnormal events;
    (E17) - determination of the type of day by comparing the quantity of abnormal events detected compared to a predefined threshold, the day being considered to be cloudy beyond this predefined threshold and sunny below this predefined threshold.
  3. Method of forecasting the electrical production of a photovoltaic device according to the previous claim, characterised in that the determination of the theoretical electricity production in clear weather (E14) is performed based on an estimation of the lighting in the plane of the photovoltaic modules in clear weather (E12) and based on the establishment of a series of ambient temperatures (E13).
  4. Method of forecasting the electrical production of a photovoltaic device according to claim 2 or 3, characterized in that the analysis (E15) of the ratio between the measured electrical power and the theoretical electrical power assuming clear weather consists in considering any value of this ratio between 0.5 and 1 to be a normal event.
  5. Method of forecasting the electrical production of a photovoltaic device according to one of claims 2 to 4, characterized in that the analysis (E16) of the derivative of the ratio between the measured electrical power and the theoretical electrical power assuming clear weather consists in considering any event corresponding to an absolute value of the differential coefficient (from the derivative) of between 0 and 0.1 to be a normal event.
  6. Method of forecasting the electrical production of a photovoltaic device according to one of claims 2 to 5, characterized in that it comprises a preliminary step for detection of natural obstacles such as mountains or buildings, that create shadows at the level of the photovoltaic modules.
  7. Method of forecasting the electrical production of a photovoltaic device according to one of previous claims, characterized in that the first part of estimating the lighting that will be received in the plane of the photovoltaic modules (1) comprises a first block (30) implementing a first calculation model to determine the horizontal lighting received by the photovoltaic device based on meteorological forecasts and a second block (40) implementing a second calculation model to determine the lighting received in the plane of the photovoltaic devices (1), in that the second part of estimating the electrical production of the photovoltaic device comprises a third block (50) implementing a third calculation model, and in that, if the past considered period is cloudy, then at least one of the first two calculation models implemented by the first (30) and/or the second (40) block is corrected according to the deviation between the true lighting, deduced from the true electrical production measured by an inverse calculation of the third calculation model of the third block (50), and the lighting forecast by the forecasting method, the third calculation model remaining unchanged.
  8. Method of forecasting the electrical production of a photovoltaic device according to the previous claim, characterized in that, if the past considered period is cloudy, the true lighting in a horizontal plane is deduced from the lighting in the plane of the photovoltaic modules which is deduced from the measurement of the true electrical production by an inverse calculation of the second and third calculation models, and in that this true lighting in the horizontal plane is compared with that forecast by the first calculation model based on meteorological forecasts, this first model being corrected according to the difference between these two lighting values, the second and third calculation models remaining unchanged.
  9. Method of forecasting the electrical production of a photovoltaic device according to the previous claim, characterized in that the first calculation model comprises weightings of several meteorological forecasts forecast at various points close to the photovoltaic modules, and in that the correction of the first model comprises a phase of evolution of the different weights of the first model.
  10. Method of forecasting the electrical production of a photovoltaic device according to one of claims 1 to 6, characterized in that the first part of estimating the lighting that will be received in the plane of the photovoltaic modules (1) comprises a first block (30) implementing a first calculation model to determine the horizontal lighting received by the photovoltaic device based on meteorological forecasts and a second block (40) implementing a second calculation model to determine the lighting received in the plane of the photovoltaic devices (1), in that the second part of estimating the electrical production of a photovoltaic device comprises a third block (50) implementing a third calculation model, and in that, if the period is sunny, then the third calculation model is corrected according to the deviation between the measured true electrical production and the electrical production forecast by the method of forecasting the electrical production, the first and second calculation models remaining unchanged.
  11. Method of forecasting the electrical production of a photovoltaic device according to one of previous claims, characterized in that the correction of the forecasting method according to the value of the measured true electrical production consists in a new calculation of one or more parameter(s) of the method, this or these calculated parameters being immediately modified for the future application of the method or stored before a periodic processing operation making it possible to modify the parameter(s) of the method, this modification relying on statistical calculations and/or based on neural networks and/or artificial intelligence and/or polynomial-type modelling.
  12. Method of forecasting the electrical production of a photovoltaic device according to one of previous claims, characterized in that the first step (E1) considers a period of a day, and determines whether this day is sunny or cloudy.
  13. Computer medium comprising a software able to implement the method of forecasting the electrical production of a photovoltaic device according to one of previous claims.
  14. Photovoltaic device comprising photovoltaic modules (1), and an element for measuring their true electrical production, characterized in that it comprises a management unit (10) implementing the method of forecasting the electrical production according to one of claims 1 to 12.
  15. Use of the method of forecasting the electrical production of a photovoltaic device according to one of claims 1 to 12 to diagnose the state of a photovoltaic device.
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